Application of Data Science in Smart Cities

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (25 May 2022) | Viewed by 8389

Special Issue Editor

Information Systems Department, ESADE Business School, Av. Pedralbes, 60-62, 08034 Barcelona, Spain
Interests: innovation; smart cities; A.I. and data science; complexity

Special Issue Information

Dear Colleagues,

In the last few decades, A.I. & big data have transformed not only organizations but markets and society as a whole. During these years, we witnessed the same promise of data-driven cities attempting to materialize. First embodied in projects such as Zero Deaths, which uses analytics aimed at eradicating fatal traffic accidents, then with the rise of A.I. applications for specific areas such as traffic management, as well as with the creation of Analytics Departments in cities, and later with the use of external Data Labs that provided the necessary expertise. Sensorization of cities has been an ongoing effort that, with its advances, has raised privacy concerns, sparking a variety of regulatory attempts.    

However, we still lack a compendium of best practices and frameworks that show both the possibilities and the limits of A.I. and data in cities together with lessons learned from the best cases. This Special Issue aims to contribute to filling this gap by advancing our understanding of the potential and the realities of A.I., analytics and big data in cities.

With this in mind, we aim to attract scholarly contributions that address (but are not limited to) the following research questions:

  • Data-driven cities: How to use data to improve city governance and services.
  • Sensors, IoT and data: Infrastructures, governance and applications.
  • The use of analytics in cities to redefine citizenship and citizen participation.
  • Governance to ensure privacy and fair use of A.I. and analytics.
  • The use of A.I., analytics and big data for the digital transformation of cities.
  • Use of data for sustainable cities.
  • The raise of citizens’ digital rights.
  • Data sharing, data trusts, data governance and cities as a platform.

Dr. Esteve Almirall
Guest Editor

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Keywords

  • data-driven cities
  • data labs
  • city analytics
  • A.I. in cities
  • city twins
  • urban analytics
  • digital rights
  • sensors in cities
  • citizen digital rights
  • data sharing in cities
  • city data infrastructures

Published Papers (2 papers)

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Research

23 pages, 5006 KiB  
Article
Possible Blockchain Solutions According to a Smart City Digitalization Strategy
by Ivica Lukić, Kruno Miličević, Mirko Köhler and Davor Vinko
Appl. Sci. 2022, 12(11), 5552; https://0-doi-org.brum.beds.ac.uk/10.3390/app12115552 - 30 May 2022
Cited by 9 | Viewed by 2238
Abstract
With advances in Information and Communication Technologies (ICT) in convergence with blockchain technology, cities have been given the opportunity to improve their services, efficiently use resources, and, thus, become Smart Cities. The main properties of blockchain technology like decentralization, immutability, transparency, consensus, and [...] Read more.
With advances in Information and Communication Technologies (ICT) in convergence with blockchain technology, cities have been given the opportunity to improve their services, efficiently use resources, and, thus, become Smart Cities. The main properties of blockchain technology like decentralization, immutability, transparency, consensus, and robustness are qualities needed for Smart City. In this paper, we propose a digitalization strategy for the City of Osijek. Smart City digitalization strategy aims to solve problems of emerging urbanization, improve administration by reducing energy and water consumption, carbon emissions, pollution, and city waste management. To develop an information system based on blockchain technology, the administration structure and the current state of information systems are analyzed, and new solutions are presented. Full article
(This article belongs to the Special Issue Application of Data Science in Smart Cities)
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27 pages, 14001 KiB  
Article
Big Data in Smart City: Management Challenges
by Mladen Amović, Miro Govedarica, Aleksandra Radulović and Ivana Janković
Appl. Sci. 2021, 11(10), 4557; https://0-doi-org.brum.beds.ac.uk/10.3390/app11104557 - 17 May 2021
Cited by 10 | Viewed by 4908
Abstract
Smart cities use digital technologies such as cloud computing, Internet of Things, or open data in order to overcome limitations of traditional representation and exchange of geospatial data. This concept ensures a significant increase in the use of data to establish new services [...] Read more.
Smart cities use digital technologies such as cloud computing, Internet of Things, or open data in order to overcome limitations of traditional representation and exchange of geospatial data. This concept ensures a significant increase in the use of data to establish new services that contribute to better sustainable development and monitoring of all phenomena that occur in urban areas. The use of the modern geoinformation technologies, such as sensors for collecting different geospatial and related data, requires adequate storage options for further data analysis. In this paper, we suggest the biG dAta sMart cIty maNagEment SyStem (GAMINESS) that is based on the Apache Spark big data framework. The model of the GAMINESS management system is based on the principles of the big data modeling, which differs greatly from standard databases. This approach provides the ability to store and manage huge amounts of structured, semi-structured, and unstructured data in real time. System performance is increasing to a higher level by using the process parallelization explained through the five V principles of the big data paradigm. The existing solutions based on the five V principles are focused only on the data visualization, not the data themselves. Such solutions are often limited by different storage mechanisms and by the ability to perform complex analyses on large amounts of data with expected performance. The GAMINESS management system overcomes these disadvantages by conversion of smart city data to a big data structure without limitations related to data formats or use standards. The suggested model contains two components: a geospatial component and a sensor component that are based on the CityGML and the SensorThings standards. The developed model has the ability to exchange data regardless of the used standard or the data format into proposed Apache Spark data framework schema. The verification of the proposed model is done within the case study for the part of the city of Novi Sad. Full article
(This article belongs to the Special Issue Application of Data Science in Smart Cities)
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